SMART INDIA HACKATHON 2024

Problem Statement ID –1554

Problem Statement Title- Smart Irrigation System for Precision Farming

Theme- Agriculture, FoodTech & Rural development

PS Category- Hardware

Team Name - Vrindavan

VRINDAVAN Proposed Solution

Smart Irrigation System for automated watering based on

sensor data and weather forecasts.

Soil Moisture Sensors to measure soil water levels

continuously and hence calculate plant water requirement.

Weather Data Integration to adjust irrigation based on

weather forecasts.

ESP32 Microcontroller to manage sensor data and control

irrigation.

Electronic Valve to control water flow to crops.

Motor powers the irrigation system.

Real-Time Monitoring with instant updates and manual

control via app

Flask Backend connects Blynk app to system components.

natural language commands

LLM Model interprets and

automates actions.

Gemini API provides additional weather and data services.

Flow sensor

@SIH Idea submission- Template 2

used to calculate the amount of water used.

TECHNICAL APPROACH

VRINDAVAN

Tec ks

Open-Source Platform: Arduino IDE for

coding.

Microcontroller Support: Writes, compiles,

uploads code.

IoT Platform: Blynk enables mobile

hardware control.

Cloud Integration: Blynk enables real-time

monitoring.

Microframework: Flask is a lightweight

web framework.

Routing: Handles flexible web request

responses.

Advanced AI Model: Google’s sophisticated

AI system.

Natural Language Processing: Generates

and understands human-like text.

Wireless Connectivity: ESP provides Wi-Fi

and Bluetooth.

Low Power Consumption: Energy-efficient

for IoT devices.

Language Model: LLMs generate and

understand text.

Versatile Applications: Chatbots,

translation, content creation.

@SIH Idea submission- Template 3

Tec

ck Methodology and process for implementation

FEASIBILITY AND VIABILITY

Potential

challenges

and risks

Technical Failures: Potential issues with sensor

accuracy or system integration.

Connectivity Issues: Possible disruptions in network

communication or data transmission.

Strategies for

overcoming these

challenges

Technical Failures: Regular calibration and robust

testing protocols.

Connectivity Issues: Implement backup communication

systems and redundancy.

VRINDAVAN

Analysis of the

feasibility of the

idea

Technical Viability:

Real-time Data: Immediate updates from sensors and

weather APIs.

Scalability: Easily expandable to larger systems or

additional fields.

System Integration: Seamless communication between

sensors, valves, and weather APIs.

Economic Justification:

Cost Savings: Reduced water usage lowers utility

expenses.

ROI: Minimal initial cost with long-term financial benefits.

Operational Practicality:

Ease of Installation: Simple setup with minimal disruption.

Maintenance: Low maintenance requirements and

straightforward troubleshooting.

UserInterface: Intuitive controls for easy system

management.

@SIH Idea submission- Template 4

IMPACT AND BENEFITS

VRINDAVAN

Consistent crop quality yields

better prices.

Qualifies for government

subsidies and financial

support.

Sustainable practices ensure

long-term agricultural viability.

Adapts to weather changes,

protecting livelihoods.

Reduces health risks from

snake bites at night.

Efficient time management

enables financial

independence.

Reduces water use and

conserves underground water.

Optimizes moisture for

healthier plants and higher

productivity.

Prevents erosion and supports

biodiversity.

Protects aquatic ecosystems

by minimizing nutrient

leaching.

Saves energy by irrigating

during off-peak hours.

Environmental

Benifits

Farmer

Benifits

Supports drought

management.

Enhances crop health and

productivity.

Minimizes disease risks from

overwatering.

Reduces labor costs with

automation.

Lowers water bills through

efficiency.

Provides real-time alerts.

Delivers analytics for crop

management.

Uses historical data for

planning.

@SIH Idea submission- Template 5

Economoical Impacts

on Farmer’s life

RESEARCH AND REFERENCES

RESEARCH REFERENCES

VRINDAVAN

An IoT Based Smart Irrigation System

@SIH Idea submission- Template 6

Smart Irrigation system using Internet of Things

Smart Irrigation System using Internet of Things (IoT)

and Machine Learning

Analysis of Internet of Things Based Agriculture

Fertilizer Nutrient Management Soil Health Irrigation

System and its Applications

Soil Moisture and Rain Prediction Based Irrigation

Controller for the Strawberry Farm of La Trinidad,

Benguet

Major Cropping Pattern Prediction in Bangladesh from

Land, Soil and Climate Data Using Machine Learning

Techniques

IEEE EXPLORE DOCUMENT